Available online at www.sciencedirect.com
ScienceDirect Procedia Engineering 118 (2015) 465 – 469
International Conference on Sustainable Design, Engineering and Construction
Developing a Three-Dimensional Geometric Framework for Greening Buildings’ Façade H. Attyaa*, A. Habibb, and D. Al-Obaybic a
University of Calgary, Department of Geomatics, 2500 University Dr. NW, Calgary,T2N 1N4,Canada Purdue University, Lyles School of Civil Engineering, 550 Stadium Mall Drive, HAMP 4108,West Lafayette, IN 47907,USA c The University of Kansas, Department of Architecture,1465 Jayhawk Blvd.Lawrence, KS 66045,USA
b
Abstract It is considerably challenging to alter the design of existing large and tall buildings to make them rely on natural energy due to many reasons. Among them is the large amount of parameters and geometric measurements required, such as height, width, plot ratio, aspect ratio, windows dimensions, etc. In this research, a new automatic algorithm is developed to model the existing buildings façade and extract several important parameters for building greening. The main contributions of this research are the automatic analysis of the digital building model and the detailed microclimatic analysis for each feature within the building façade. The developed algorithm starts with an automatic digital three-dimensional modeling of the building façade, followed by an automated extraction of the required parameters to alter the façade design such as orientation, height, and width. Results show that the proposed method offers very high accuracy and time/cost effective way for parametric modeling of the existing buildings’ façade. © Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license ©2015 2015The The Authors. Published by Elsevier Ltd. (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of organizing committee of the International Conference on Sustainable Design, Engineering Peer-review under responsibility of organizing committee of the International Conference on Sustainable Design, Engineering and and Construction Construction 2015 2015. Keywords: Green Buildings, LiDAR, Façade Analysis, Parametric Design
* Corresponding author. Tel.: +1-403-220-4983; fax: +1-403-284-1980. E-mail address:
[email protected]
1877-7058 © 2015 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of organizing committee of the International Conference on Sustainable Design, Engineering and Construction 2015
doi:10.1016/j.proeng.2015.08.448
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1. Introduction In order to design green or sustainable architecture, architects should meet present needs without compromising the ability of future generations to freely encounter their own requirements. To achieve this fundamental concept, architects should consider their design as a research process and look for the sensitive aspects that define the green architecture. Such aspects include, but not limited to: 1) Solar radiation as a source of lighting, natural heating and energy [1]. 2) The building proportions such as aspect ratio, and mass to void ratio [2]. 3) The orientation of a building with respect to prevailing wind and sun [3]. Refurbishing and greening existing buildings is usually more challenging than designing new buildings. Not only because of site and existing structure constraints, but also because of the numerous measurements required which are not easy to collect especially when dealing with large and complex buildings. The proposed method in this paper aims to address this issue by providing an automatic algorithm to model existing buildings and extract the required measurement. The paper is organized in five parts: starting with an introduction in the first part, followed by a summarized analysis for the main related work in the second part. The third part deals with research methods, then results and discussion are in the fourth part and finally the concluded message is in the fifth part. 2. Related work Most of the relevant work to this research could be classified into two categories: the first deals with the environmental and micro-climatic analysis of buildings and urban spaces, and the second deals with analysis of the building design itself. Most of the research in the first category analyzes the relationships between the built environment and the surrounding micro-climate through simulation tools. Dorer et al. analyzed the impact of the urban micro-climate on the energy demand of buildings [4]. Shishegar studied the effects of street geometry namely the width/height ratio and orientation on the airflow and solar access in urban canyons [5]. De la Flor et al. investigated the performance of different building envelop elements with response to changing the outdoor environmental conditions [6]. In common among most of the work in the first category is that simulation is being used instead of real data which in the authors’ opinion was because of the difficulties associated with field measurements. This opinion is more supported when the second group of literature was reviewed. Very few researches were found to deal with analysis of the building design itself after being modeled. Ripperda and Brenner studied the application of shape grammar concepts to help in façade reconstruction [7]. Shape grammar provides information about the structure of the façade design that is useful to predict the missing parts of the building façade during the surveying process due to occlusions. A study by Li et al. investigated the possibility of generating building information model (BMI) from laser scanning point cloud [8]. Attya and Habib investigated different options for building façade mapping based on the accuracy of the photogrammetric reconstruction process without any geometric analysis of the building façade design [9]. As a conclusion from the aforementioned discussion is the up to the best knowledge of the authors, there is no research that deals with the extraction of the building parameters that could essential for building environmental design. 3. Methodology Laser scanning point cloud data is used in this research to obtain the building measurements. The point cloud is a set of millions of 3D points on the building façade that measured by a static terrestrial laser scanner, a surveying instrument that measure the range between its setup location and millions of points on the targeted object based on the difference in time between the fired and reflected laser beam. It is assumed in this research that a digital building model (DBM) is available and the collected laser point cloud is registered to its coordinate system. There is, usually, a very limited control on the extent of the area scanned with the laser scanner, i.e., many objects that are not of interest could be recorded. Therefore a geometric analysis is required to recognize the features of interest and to extract the required parameters. The first step is to filter out the ground points. In this research, the histogram of the Z-coordinate of the laser-scanned points is computed then the biggest class in the histogram will represent all the ground points assuming that the ground points should not have great change in the Z-coordinate. The second step is to recognize the building of interest in the raw point cloud by determining the building façade plane using the
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building corners from the DBM as shown in Fig. 1, then grouping all the points that fall within certain normal distance from the façade plane to represent the building of interest. The normal distance threshold is determined as a function of the design of the building façade itself.
Fig. 1 determining the building facade plane using the building corners in the DBM
The third step is to segment the points that were already classified as the building of interest into disjoint planar features. Parameter-domain segmentation approach implemented by Lari and Habib was used in this research to determine the planar features within the dataset [10]. The dataset is ready now to compute the parameters that are required for environmental analysis of the building façade which is the fourth step in the proposed methodology. The general orientation of the building could be computed as the aspect of the normal vector of the façade plane which is already computed from the DBM in the second step. The aspect equation is: ݐܿ݁ݏܣൌ ͳͺͲ ି݊ܽݐଵ ሺ ሻ where a and b are the elements of the normal vector. This equation could also be used to compute the orientation of each planar feature within the building façade. The width of the building façade could be computed from the corresponding corners in the DBM: ݄ݐ݀݅ݓൌ ඥሺܺଶ െ ܺଵ ሻଶ ሺܻଶ െ ܻଵ ሻଶ where X and Y are the coordinates of the building façade corners from the DBM. The height of the building is computed as the difference between the largest Z-coordinate of the corresponding corners from the DBM and the smallest Z-coordinate of the dataset.
4. Results and discussion Fig. 2 shows that the proposed algorithm is successful in filtering out the ground points and recognizing the building of interest. The white gaps in the figure were caused by the occlusion due to trees between the scanner location and the building. This could be dealt with by applying the shape grammar concept which is left for future work. The width of the building façade was computed to be 30.71 meters differs from the measured value by 23 cm which is a very promising accuracy. The height was computed to be 19.43 meters with a difference of 28 cm from the measured height. The accuracy in both vertical and horizontal directions is almost equivalent and within the reported accuracy of the DBM. In terms of the orientation: the general orientation of the building was computed to be 91o from the true north (Azimuth) which is pretty close to the measured direction using magnetic compass. Looking to the segmented façade in detail reveals three groups of planar features with orientations of 50 o, 83 o, and 92 o which quite identical with the façade design as shown in Fig. 3.
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Fig. 2: (a) The raw dataset. (b) The non-ground points. (c) The building of interest. (d) The segmented points into planar features
Fig. 3: Part of The segmented data showing the three groups of computed orientations of the planar features within the facade
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5. Conclusions A new method is proposed in this research to analyse the design of existing buildings and develop a parametric framework for environmental design. The proposed methods were successful in automatically modelling the building and extract some of the environmental parameters in time and cost effective manner. Width, height, and orientation were extracted so far. The future research will be focusing on increasing the accuracy and extract more parameters such as aspect ratio, surface/volume ratio, biomass, individual trees, and green landscape automatic recognition. 6. Acknowledgements This research is funded by the University of Baghdad, Schulich School of Engineering, and Geomatics Department at the University of Calgary. References W. M. Marsh, Landscape planning: Environmental applications, 5th ed. Hoboken, NJ: John Wiley & Sons, 2010. [2] C. Ratti, N. Baker, and K. Steemers, “Energy consumption and urban texture,” Energy Build., vol. 37, no. 7, pp. 762–776, Jul. 2005. [3] M. Aboul-Naga, K. A. Al-Sallal, and R. E. Diasty, “Impact of City Urban Patterns on Building Energy Use: Al-Ain City as a Case Study for Hot-Arid Climates,” Archit. Sci. Rev., vol. 43, no. 3, pp. 147–158, Sep. 2000. [4] V. Dorer, J. Allegrini, K. Orehounig, P. Moonen, G. Upadhyay, J. Kämpf, and J. Carmeliet, “MODELLING THE URBAN MICROCLIMATE AND ITS IMPACT ON THE ENERGY DEMAND OF BUILDINGS AND BUILDING CLUSTERS,” in Proceedings of BS2013, Chambéry, France, 2013. [5] N. Shishegar, “Street Design and Urban Microclimate: Analyzing the Effects of Street Geometry and Orientation on Airflowand Solar Access in Urban Canyons,” J. Clean Energy Technol., vol. 1, no. 1, pp. 52– 56, Jan. 2013. [6] F. J. S. de la Flor, J. M. S. Lissén, and S. Á. Domínguez, “A new methodology towards determining building performance under modified outdoor conditions,” Build. Environ., vol. 41, no. 9, pp. 1231–1238, Sep. 2006. [7] N. Ripperda and C. Brenner, “Application of a formal grammar to facade reconstruction in semiautomatic and automatic environments,” in Proc. of the 12th AGILE Conference on GIScience, Hannover, Germany, 2009, pp. 1–12. [8] S. Li, J. Isele, and G. Bretthauer, “Proposed methodology for generation of building information model with laserscanning,” Tsinghua Sci. Technol., vol. 13, no. S1, pp. 138–144, Oct. 2008. [9] H. Attya and A. Habib, “OPTIONS FOR MEDIUM-ACCURACY ARCHITECTURAL FACADES MAPPING FROM TERRESTRIAL PHOTOGRAMMETRY,” in ASPRS 2013 Proceedings, Baltimore, MA, 2013. [10] Z. Lari and A. Habib, “An adaptive approach for the segmentation and extraction of planar and linear/cylindrical features from laser scanning data,” ISPRS J. Photogramm. Remote Sens., Jan. 2014. [1]
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